Suppr超能文献

使用M型或人工智能技术通过肋下和经肝成像评估下腔静脉可塌陷性:一项针对健康志愿者的前瞻性研究。

Assessment of the inferior vena cava collapsibility from subcostal and trans-hepatic imaging using both M-mode or artificial intelligence: a prospective study on healthy volunteers.

作者信息

Sanfilippo Filippo, La Via Luigi, Dezio Veronica, Santonocito Cristina, Amelio Paolo, Genoese Giulio, Astuto Marinella, Noto Alberto

机构信息

Department of Anaesthesia and Intensive Care, A.O.U. Policlinico-San Marco, site "Policlinico G. Rodolico", Via S. Sofia N 78, 95123, Catania, Italy.

School of Anaesthesia and Intensive Care, University Hospital "G. Rodolico", University of Catania, 95123, Catania, Italy.

出版信息

Intensive Care Med Exp. 2023 Apr 3;11(1):15. doi: 10.1186/s40635-023-00505-7.

Abstract

PURPOSE

Assessment of the inferior vena cava (IVC) respiratory variation may be clinically useful for the estimation of fluid-responsiveness and venous congestion; however, imaging from subcostal (SC, sagittal) region is not always feasible. It is unclear if coronal trans-hepatic (TH) IVC imaging provides interchangeable results. The use of artificial intelligence (AI) with automated border tracking may be helpful as part of point-of-care ultrasound but it needs validation.

METHODS

Prospective observational study conducted in spontaneously breathing healthy volunteers with assessment of IVC collapsibility (IVCc) in SC and TH imaging, with measures taken in M-mode or with AI software. We calculated mean bias and limits of agreement (LoA), and the intra-class correlation (ICC) coefficient with their 95% confidence intervals.

RESULTS

Sixty volunteers were included; IVC was not visualized in five of them (n = 2, both SC and TH windows, 3.3%; n = 3 in TH approach, 5%). Compared with M-mode, AI showed good accuracy both for SC (IVCc: bias - 0.7%, LoA [- 24.9; 23.6]) and TH approach (IVCc: bias 3.7%, LoA [- 14.9; 22.3]). The ICC coefficients showed moderate reliability: 0.57 [0.36; 0.73] in SC, and 0.72 [0.55; 0.83] in TH. Comparing anatomical sites (SC vs TH), results produced by M-mode were not interchangeable (IVCc: bias 13.9%, LoA [- 18.1; 45.8]). When this evaluation was performed with AI, such difference became smaller: IVCc bias 7.7%, LoA [- 19.2; 34.6]. The correlation between SC and TH assessments was poor for M-mode (ICC = 0.08 [- 0.18; 0.34]) while moderate for AI (ICC = 0.69 [0.52; 0.81]).

CONCLUSIONS

The use of AI shows good accuracy when compared with the traditional M-mode IVC assessment, both for SC and TH imaging. Although AI reduces differences between sagittal and coronal IVC measurements, results from these sites are not interchangeable.

摘要

目的

评估下腔静脉(IVC)呼吸变异对于估计液体反应性和静脉充血可能具有临床意义;然而,从肋下(SC,矢状面)区域进行成像并不总是可行的。目前尚不清楚冠状面经肝(TH)IVC成像是否能提供可互换的结果。在床旁超声检查中使用具有自动边界跟踪功能的人工智能(AI)可能会有所帮助,但需要进行验证。

方法

对自主呼吸的健康志愿者进行前瞻性观察研究,评估SC和TH成像中的IVC可塌陷性(IVCc),采用M型测量或使用AI软件进行测量。我们计算了平均偏差和一致性界限(LoA),以及组内相关系数(ICC)及其95%置信区间。

结果

纳入60名志愿者;其中5人未观察到IVC(n = 2,SC和TH窗口均未观察到,3.3%;n = 3在TH方法中未观察到,5%)。与M型相比,AI在SC(IVCc:偏差 - 0.7%,LoA [- 24.9;23.6])和TH方法(IVCc:偏差3.7%,LoA [- 14.9;22.3])中均显示出良好的准确性。ICC系数显示出中等可靠性:SC为0.57 [0.36;0.73],TH为0.72 [0.55;0.83]。比较解剖部位(SC与TH),M型产生的结果不可互换(IVCc:偏差13.9%,LoA [- 18.1;45.8])。当使用AI进行此评估时,这种差异变小:IVCc偏差7.7%,LoA [- 19.2;34.6]。M型的SC和TH评估之间的相关性较差(ICC = 0.08 [- 0.18;0.34]),而AI的相关性中等(ICC = 0.69 [0.52;0.81])。

结论

与传统的M型IVC评估相比,AI在SC和TH成像中均显示出良好的准确性。虽然AI减少了矢状面和冠状面IVC测量之间的差异,但这些部位的结果不可互换。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7d1/10068684/ebe845434f73/40635_2023_505_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验